Morphological diversity of single neurons in molecularly defined cell types

Single-cell and spatial omics: exploring hypothalamic heterogeneity

Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.

Single-nucleus and spatial signatures of the brainstem in normal brain and mild traumatic brain injury in male mice

The mammalian brainstem is particularly vulnerable to mild traumatic brain injury (mTBI), which is associated with prolonged autonomic dysfunction and coma. The spatial cellular connections within the brainstem or the mechanisms underlying its response to injury have been underestimated. Here, we performed single-nucleus RNA sequencing with spatial transcriptome sequencing in both normal and mTBI brainstems in male mice, revealing thirty-five neuron and non-neuron clusters. Typically, we identified subtypes of neurons that co-release multiple neurotransmitters, especially in the sagittal midline of the brainstem. Spatially adjacent neurons sharing similar gene expression patterns. The brainstem's response to mTBI has two features: (1) Oligodendrocytes around the fourth ventricle exhibit widespread disconnection at 1-h post-injury, and (2) Injury-related noradrenergic neurons, particularly in their interaction with neurons located in theIRt and the Sol. These findings provides a reference for further integrative investigations of cellular and circuit functions of brainstem.

A suite of enhancer AAVs and transgenic mouse lines for genetic access to cortical cell types

The mammalian cortex is comprised of cells classified into types according to shared properties. Defining the contribution of each cell type to the processes guided by the cortex is essential for understanding its function in health and disease. We use transcriptomic and epigenomic cortical cell-type taxonomies from mouse and human to define marker genes and putative enhancers and create a large toolkit of transgenic lines and enhancer adeno-associated viruses (AAVs) for selective targeting of cortical cell populations. We report creation and evaluation of fifteen transgenic driver lines, two reporter lines, and >1,000 different enhancer AAV vectors covering most subclasses of cortical cells. The tools reported here have been made publicly available, and along with the scaled process of tool creation, evaluation, and modification, they will enable diverse experimental strategies toward understanding mammalian cortex and brain function.

Reveal the mechanism of brain function with fluorescence microscopy at single-cell resolution: from neural decoding to encoding

As a key pathway for understanding behavior, cognition, and emotion, neural decoding and encoding provide effective tools to bridge the gap between neural mechanisms and imaging recordings, especially at single-cell resolution. While neural decoding aims to establish an interpretable theory of how complex biological behaviors are represented in neural activities, neural encoding focuses on manipulating behaviors through the stimulation of specific neurons. We thoroughly analyze the application of fluorescence imaging techniques, particularly two-photon fluorescence imaging, in decoding neural activities, showcasing the theoretical analysis and technological advancements from imaging recording to behavioral manipulation. For decoding models, we compared linear and nonlinear methods, including independent component analysis, random forests, and support vector machines, highlighting their capabilities to reveal the intricate mapping between neural activity and behavior. By employing synthetic stimuli via optogenetics, fundamental principles of neural encoding are further explored. We elucidate various encoding types based on different stimulus paradigms-quantity encoding, spatial encoding, temporal encoding, and frequency encoding-enhancing our understanding of how the brain represents and processes information. We believe that fluorescence imaging-based neural decoding and encoding techniques have deepened our understanding of the brain, and hold great potential in paving the way for future neuroscience research and clinical applications.

Developmental dynamics of marmoset prefrontal cortical SST and PV interneuron networks highlight primate-specific features

The primate prefrontal cortex (PFC) undergoes protracted postnatal development, crucial for the emergence of cognitive control and executive function. Central to this maturation are inhibitory interneurons (INs), particularly parvalbumin-expressing (PV+) and somatostatin-expressing (SST+) subtypes, which regulate cortical circuit timing and plasticity. While rodent models have provided foundational insights into IN development, the trajectory of postmigratory maturation in primates remains largely uncharted. In this study, we characterized the expression of PV, SST, the chloride transporter KCC2, and the ion channels Kv3.1b and Nav1.1 across six PFC regions (areas 8aD, 8aV, 9, 46, 11 and 47L) in the postnatal marmoset. We report a prolonged maturation of PV+ INs into adolescence, accompanied by progressive upregulation of ion channels that support high-frequency firing. In contrast, SST+ INs show a postnatal decline in density, diverging from rodent developmental patterns. These findings reveal distinct, cell type-specific maturation dynamics in the primate PFC and offer a developmental framework for understanding how inhibitory circuit refinement may underlie vulnerability to neurodevelopmental disorders.

Toward a probabilistic definition of neural cell types

A classical view of cell type relies on a definite set of stable properties that are critical for brain functions. Single-cell technologies led to an extensive multimodal characterization of nervous systems and perhaps achieved one of Santiago Ramón y Cajal's dreams: to unveil a comprehensive view of the brain composition. While global analyses of brain structures highlight a degree of mesoscale stereotypy, a finer-scale resolution of brain composition shows significant variance in essential neural cellular phenotypes, including morphology, gene expression, electrophysiology, and connectivity. This highlights the need for novel conceptualization of the definition of a neural "cell type." The challenge of modern neural classification is thus to integrate various distinct cellular properties into a unifying descriptor.

Reconstruction of Single-Neuron Projectomes in Mice

Reconstructing single-neuron projectomes is essential for mapping the mesoscopic connectome and eventually for understanding brain-wide connectivity and diverse brain functions. The combination of sparse labeling techniques and large-scale and high-resolution optical imaging technologies has been revolutionizing the brain-wide reconstruction of single-neuron morphologies, as exemplified by the dataset for over 10,100 single-neuron projectomes of hippocampal neurons. Here, we illustrate a comprehensive protocol for large-scale single-neuron reconstruction in the mouse brain. This includes key steps and examples in imaging data preprocessing, neurite tracing, and registration into a template brain. These procedures enable efficient and accurate large-scale morphological reconstruction of single neurons in the mouse brain. Key features • Rigorous and effective single-neuron reconstruction from raw imaging data. • Multi-person tracing and quality control for the accuracy of single-neuron tracing results. • Precise image registration based on landmark drawings of selected brain regions.

Toward Principles of Brain Network Organization and Function

The brain is immensely complex, with diverse components and dynamic interactions building upon one another to orchestrate a wide range of behaviors. Understanding patterns of these complex interactions and how they are coordinated to support collective neural function is critical for parsing human and animal behavior, treating mental illness, and developing artificial intelligence. Rapid experimental advances in imaging, recording, and perturbing neural systems across various species now provide opportunities to distill underlying principles of brain organization and function. Here, we take stock of recent progress and review methods used in the statistical analysis of brain networks, drawing from fields of statistical physics, network theory, and information theory. Our discussion is organized by scale, starting with models of individual neurons and extending to large-scale networks mapped across brain regions. We then examine organizing principles and constraints that shape the biological structure and function of neural circuits. We conclude with an overview of several critical frontiers, including expanding current models, fostering tighter feedback between theory and experiment, and leveraging perturbative approaches to understand neural systems. Alongside these efforts, we highlight the importance of contextualizing their contributions by linking them to formal accounts of explanation and causation.

Projectome-based characterization of hypothalamic peptidergic neurons in male mice

The hypothalamus coordinately regulates physiological homeostasis and innate behaviors, yet the detailed arrangement of hypothalamic axons remains unclear. Here we mapped the whole-brain projections of over 7,000 hypothalamic neurons expressing distinct neuropeptides in male mice, identifying 2 main classes and 31 types using single-neuron projectome analysis. These classes/types exhibited regionally biased soma distribution and specific neuropeptide enrichment. Notably, many projectome types extended long-range axon collaterals to distinct brain regions, allowing single axons to co-regulate multiple targets. We uncovered topographic organization of certain peptidergic axons at specific targets, along with diverse single-neuron projectome patterns in Orexin, Agrp and Pomc populations. Furthermore, hypothalamic peptidergic neurons showed correlated innervation of subdomains in the periaqueductal gray and organized into modular subnetworks within the hypothalamus, providing a structural basis for coordinated outputs. This dataset highlights the complexity of hypothalamic axonal projections and lays a foundation for future investigation of the circuit mechanisms underlying hypothalamic functions.

NeuroXiv: AI-powered open databasing and dynamic mining of brain-wide neuron morphometry

Neuron morphology has been extensively reconstructed at the whole-brain scale by various projects in recent years. Here, to facilitate interactive exploration in a standardized and scalable manner, we introduce NeuroXiv (neuroxiv.org), a large-scale database containing 175,149 reconstructed neuron morphologies mapped to the Common Coordinate Framework Version 3 (CCFv3). In addition, NeuroXiv incorporates an AI-powered mining engine (AIPOM) for dynamic, user-specific data mining, delivering enhanced performance via a custom client program.

A Multi-Scale Neuron Morphometry Dataset from Peta-voxel Mouse Whole-Brain Images

Neuron morphology and sub-neuronal patterns offer vital insights into cell typing and the structural organization of brain networks. The community-collaborative BRAIN Initiative Cell Census Network (BICCN) project has yielded a vast amount of whole-brain imaging data. However, reconstructing multi-scale neuron morphometry at a whole-brain scale requires not only the integration of diverse hardware devices, tools, and algorithms but also a dedicated production workflow. To address these challenges, we developed a cloud-based, collaborative platform capable of handling peta-scale imaging data. Using this platform, we generated the largest multi-scale morphometry dataset from hundreds of sparsely labeled mouse brains. The morphometry dataset comprises 182,497 annotated cell bodies, 15,441 locally traced morphologies, and 1,876 fully reconstructed morphologies. We also identified sub-neuronal arborizations for both axons and dendrites, along with the primary axonal tracts connecting them. In addition, we identified 2.63 million putative boutons. All morphometric data were registered to the Allen Common Coordinate Framework (CCF) atlas. The morphometry dataset has proven to be an invaluable resource for whole-brain cross-scale morphological studies in mouse.

Modular strategies for spatial mapping of diverse cell type data of the mouse brain

Large-scale, international collaborative efforts by members of the BRAIN Initiative Cell Census Network (BICCN) consortium are aggregating the most comprehensive reference database to date for diverse cell type profiling of the mouse brain, which encompasses over 40 different multi-modal profiling techniques from more than 30 research groups. One central challenge for this integrative effort has been the need to map these unique datasets into common reference spaces such that the spatial, structural, and functional information from different cell types can be jointly analyzed. However, significant variation in the acquisition, tissue processing, and imaging techniques across data types makes mapping such diverse data a multifarious problem. Different data types exhibit unique tissue distortion and signal characteristics that precludes a single mapping strategy from being generally applicable across all cell type data. Tailored mapping approaches are often needed to address the unique barriers present in each modality. This work highlights modular atlas mapping strategies developed across separate BICCN studies using the Advanced Normalization Tools Ecosystem (ANTsX) to map spatial transcriptomic (MERFISH) and high-resolution morphology (fMOST) mouse brain data into the Allen Common Coordinate Framework (AllenCCFv3), and developmental (MRI and LSFM) data into the Developmental Common Coordinate Framework (DevCCF). We discuss common mapping strategies that can be shared across modalities and driven by specific challenges from each data type. These mapping strategies include novel open-source contributions that are made publicly available through ANTSX. These include 1) a velocity flow-based approach for continuously mapping developmental trajectories such as that characterizing the DevCCF and 2) an automated framework for determining structural morphology solely through the leveraging of publicly resources. Finally, we provide general guidance to aid investigators to tailor these strategies to address unique data challenges without the need to develop additional specialized software.

Layer-specific input to medial prefrontal cortex is linked to stress susceptibility

Stress response is essential for adapting to an ever-changing environment. However, the mechanisms that render some individuals susceptible to stress are poorly understood. While chronic stress is known to induce dendritic atrophy and spine loss in medial prefrontal cortex (mPFC), its impact on synapses made by long-range projections terminating on the mPFC remains unknown. Here, we labeled synapses on male mouse mPFC dendrites formed by ventral hippocampus (VH), basolateral amygdala (BLA) and ventral tegmental area (VTA) long-range afferents using different-colored eGRASP constructs. We obtained multispectral 3D-images of the mPFC covering all cortical laminae, and automatically segmented the dendrites and synapses. In layer II/III, the relative abundances and spatial organizations of VH-mPFC and BLA-mPFC synapses changed similarly in stress resilient (SR) and stress susceptible (SS) mice when compared to stress naïve (SN) mice. In layers Vb and VI, on the other hand, the percentage of BLA-mPFC synapses increased and that of VH-mPFC decreased only in SS mice. Moreover, the distances of VH synapses to their corresponding closest BLA synapses decreased and the distances of BLA synapses to their corresponding closest VH synapses increased in the SS group. Consistently, the percentage of single dendritic segments receiving input from multiple brain regions increased in the SS group, suggesting that long-range synaptic inputs to deep layers of mPFC were disorganized in SS mice. Our findings demonstrate afferent- and lamina-specific differential reorganization of synapses between different stress phenotypes, suggesting specific roles for different long-range projections in mediating the stress response.

Single-neuron projectome reveals organization of somatosensory ascending pathways in the mouse brain

Relay of multimodal somatosensory information from the spinal cord to the brain is critical for sensory perception, but the underlying circuit organization remains unclear. We have reconstructed mouse cervical spinal projection neurons at single-cell resolution and identified 19 projectome-defined subtypes exhibiting diverse projection patterns. We also reconstructed the brain-wide axonal projections of central relay neurons that receive direct spinal inputs at the single-cell resolution. We discovered parallel, divergent, and convergent projection patterns for spinal projection neurons and central relay neurons. Our results revealed the diverse pathways channeling spinal information to the cortex. Furthermore, we identified parallel lateral and medial spinal-superior colliculus-brainstem pathways, which could be involved in orienting and defensive behaviors, respectively. These data allowed us to construct a wiring diagram for ascending somatosensory pathways with projectome-defined subtype resolution. Our single-cell projectome analysis provided a new framework for understanding the complex neural circuitry underlying coordinated processing of diverse somatosensory modalities.

A parallel tonotopically arranged thalamocortical circuit for sound processing

The perception of the sensory world in mammals requires information flow from the thalamus to the cortex. Although the first-order sensory thalamus and its surrounding nuclei are considered the major hub for feedforward thalamocortical transmission, it remains unknown whether any other thalamic input could also contribute to this transmission. We found a thalamic region, the basal region of the ventromedial nucleus of the thalamus (bVM), that sends dense, tonotopically arranged projections to auditory cortex (AuC) fields. Silencing these AuC-projecting neurons severely impaired the mouse's ability to discriminate sound frequencies. These projections exhibited strong frequency-tuning preferences that matched the cortical tonotopic map. Moreover, bVM inputs were excitatory and primarily terminated on neuron-derived neurotrophic factor-positive interneurons in cortical layer 1. Silencing these inputs significantly reduced sound-evoked responses of AuC neurons. Our results reveal a non-canonical, tonotopically arranged thalamic input to cortical layer 1 that contributes to sound processing, in parallel to the classic auditory thalamocortical pathway.

Spatially informed graph transformers for spatially resolved transcriptomics

Spatially resolved transcriptomics (SRT) has emerged as a powerful technique for mapping gene expression landscapes within spatial contexts. However, significant challenges persist in effectively integrating gene expression with spatial information to elucidate the heterogeneity of biological tissues. Here, we present a Spatially informed Graph Transformers framework, SpaGT, which leverages both node and edge channels to model spatially aware graph representation for denoising gene expression and identifying spatial domains. Unlike conventional graph neural networks, which rely on static, localized convolutional aggregation, SpaGT employs a structure-reinforced self-attention mechanism that iteratively evolves topological structural information and transcriptional signal representation. By replacing graph convolution with global self-attention, SpaGT enables the integration of both global and spatially localized information, thereby improving the detection of fine-grained spatial domains. We demonstrate that SpaGT achieves superior performance in identifying spatial domains and denoising gene expression data across diverse platforms and species. Furthermore, SpaGT facilitates the discovery of spatially variable genes with significant prognostic potential in cancer tissues. These findings establish SpaGT as a powerful tool for unraveling the complexities of biological tissues.

Connectivity of single neurons classifies cell subtypes in mouse brains

Classification of single neurons at a brain-wide scale is a way to characterize the structural and functional organization of brains. Here we acquired and standardized a large morphology database of 20,158 mouse neurons and generated a potential connectivity map of single neurons based on their dendritic and axonal arbors. With such an anatomy-morphology-connectivity mapping, we defined neuron connectivity subtypes for neurons in 31 brain regions. We found that cell types defined by connectivity show distinct separation from each other. Within this context, we were able to characterize the diversity in secondary motor cortical neurons, and subtype connectivity patterns in thalamocortical pathways. Our findings underscore the importance of connectivity in characterizing the modularity of brain anatomy at the single-cell level. These results highlight that connectivity subtypes supplement conventionally recognized transcriptomic cell types, electrophysiological cell types and morphological cell types as factors to classify cell classes and their identities.

Inkjet-printed transparent electrodes: Design, characterization, and initial in vivo evaluation for brain stimulation

Electrical stimulation is a powerful tool for investigating and modulating brain activity, as well as for treating neurological disorders. However, understanding the precise effects of electrical stimulation on neural activity has been hindered by limitations in recording neuronal responses near the stimulating electrode, such as stimulation artifacts in electrophysiology or obstruction of the field of view in imaging. In this study, we introduce a novel stimulation device fabricated from conductive polymers that is transparent and therefore compatible with optical imaging techniques. The device is manufactured using a combination of microfabrication and inkjet printing techniques and is flexible, allowing better adherence to the brain's natural curvature. We characterized the electrical and optical properties of the electrodes, focusing on the trade-off between the maximum current that can be delivered and optical transmittance. We found that a 1 mm diameter, 350 nm thick PEDOT:PSS electrode could be used to apply a maximum current of 130 μA while maintaining 84% transmittance (approximately 50% under 2-photon imaging conditions). We then evaluated the electrode performance in the brain of an anesthetized mouse by measuring the electric field with a nearby recording electrode and found values up to 30 V/m. Finally, we combined experimental data with a finite-element model of the in vivo experimental setup to estimate the distribution of the electric field underneath the electrode in the mouse brain. Our findings indicate that the device can generate an electric field as high as 300 V/m directly beneath the electrode, demonstrating its potential for studying and manipulating neural activity using a range of electrical stimulation techniques relevant to human applications. Overall, this work presents a promising approach for developing versatile new tools to apply and study electrical brain stimulation.

NEURD offers automated proofreading and feature extraction for connectomics

We are in the era of millimetre-scale electron microscopy volumes collected at nanometre resolution1,2. Dense reconstruction of cellular compartments in these electron microscopy volumes has been enabled by recent advances in machine learning3-6. Automated segmentation methods produce exceptionally accurate reconstructions of cells, but post hoc proofreading is still required to generate large connectomes that are free of merge and split errors. The elaborate 3D meshes of neurons in these volumes contain detailed morphological information at multiple scales, from the diameter, shape and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting these features can require substantial effort to piece together existing tools into custom workflows. Here, building on existing open source software for mesh manipulation, we present Neural Decomposition (NEURD), a software package that decomposes meshed neurons into compact and extensively annotated graph representations. With these feature-rich graphs, we automate a variety of tasks such as state-of-the-art automated proofreading of merge errors, cell classification, spine detection, axonal-dendritic proximities and other annotations. These features enable many downstream analyses of neural morphology and connectivity, making these massive and complex datasets more accessible to neuroscience researchers.

Single-cell spatial transcriptome atlas and whole-brain connectivity of the macaque claustrum

Claustrum orchestrates brain functions via its connections with numerous brain regions, but its molecular and cellular organization remains unresolved. Single-nucleus RNA sequencing of 227,750 macaque claustral cells identified 48 transcriptome-defined cell types, with most glutamatergic neurons similar to deep-layer insular neurons. Comparison of macaque, marmoset, and mouse transcriptomes revealed macaque-specific cell types. Retrograde tracer injections at 67 cortical and 7 subcortical regions defined four distinct distribution zones of retrogradely labeled claustral neurons. Joint analysis of whole-brain connectivity and single-cell spatial transcriptome showed that these four zones containing distinct compositions of glutamatergic (but not GABAergic) cell types preferentially connected to specific brain regions with a strong ipsilateral bias. Several macaque-specific glutamatergic cell types in ventral vs. dorsal claustral zones selectively co-projected to two functionally related areas-entorhinal cortex and hippocampus vs. motor cortex and putamen, respectively. These data provide the basis for elucidating the neuronal organization underlying diverse claustral functions.

Cell-class-specific orofacial motor maps in mouse neocortex

Cortical motor maps represent fundamental organizing principles for voluntary motor control,1 yet their underlying structure remains poorly understood, including regions of sensory2,3 and parietal cortex,4 as well as the classical frontal motor cortex. To understand how anatomically distinct cortical areas are organized into functional units for controlling movements, here, we refined cortical motor maps by selectively stimulating genetically defined subpopulations of excitatory neurons. Surprisingly, we found spatially segregated modules in orofacial motor maps by optogenetically stimulating different classes of cortical excitatory neurons. The overall motor map for jaw opening revealed by stimulating all classes of excitatory neurons spanned the anterior lateral cortex broadly. By contrast, the jaw-opening motor maps of specific genetically defined cell classes were focalized either in primary motor, secondary motor, or primary somatosensory areas within the overall jaw-opening motor map of all excitatory neurons, demonstrating cell-class-specific motor map modules. Simultaneous wide-field calcium imaging revealed activity propagation from optically stimulated motor map modules to the primary motor area correlating with movement vigor. The motor map modules were largely stable across lick motor learning with important exceptions indicating cell-class-specific expansion into other module zones. Our data suggest that distinct cell-class-specific modules interacting across sensorimotor cortices might contribute to controlling orofacial movement.

Multimodal insights into adult neurogenesis: An integrative review of multi-omics approaches

Adult neural stem cells divide to produce neurons that migrate to preexisting neuronal circuits in a process named adult neurogenesis. Adult neurogenesis is one of the most exciting areas of current neuroscience, and it may be involved in a range of brain functions, including cognition, learning, memory, and social and behavior changes. While there is a growing number of multi-omics studies on adult neurogenesis, generalized analyses from a multi-omics perspective are lacking. In this review, we summarize studies related to genomics, metabolomics, proteomics, epigenomics, transcriptomics, and microbiomics of adult neurogenesis, and then discuss their future research priorities and potential neighborhoods. This will provide theoretical guidance and new directions for future research on adult neurogenesis.

The Trail of Axonal Protein Synthesis: Origins and Current Functional Landscapes

Local protein synthesis (LPS) in axons is now recognized as a physiological process, participating both in the maintenance of axonal function and diverse plastic phenomena. In the last decades of the 20th century, the existence and function of axonal LPS were topics of significant debate. Very early, axonal LPS was thought not to occur at all and was later accepted to play roles only during development or in response to specific conditions. However, compelling evidence supports its essential and pervasive role in axonal function in the mature nervous system. Remarkably, in the last five decades, Uruguayan neuroscientists have contributed significantly to demonstrating axonal LPS by studying motor and sensory axons of the peripheral nervous system of mammals, as well as giant axons of the squid and the Mauthner cell of fish. For LPS to occur, a highly regulated transport system must deliver the necessary macromolecules, such as mRNAs and ribosomes. This review discusses key findings related to the localization and abundance of axonal mRNAs and their translation levels, both in basal states and in response to physiological processes, such as learning and memory consolidation, as well as neurodevelopmental and neurodegenerative disorders, including Alzheimer's disease, autism spectrum disorder, and axonal injury. Moreover, we discuss the current understanding of axonal ribosomes, from their localization to the potential roles of locally translated ribosomal proteins, in the context of emerging research that highlights the regulatory roles of the ribosome in translation. Lastly, we address the main challenges and open questions for future studies.

Transcriptomic neuron types vary topographically in function and morphology

Neuronal phenotypic traits such as morphology, connectivity and function are dictated, to a large extent, by a specific combination of differentially expressed genes. Clusters of neurons in transcriptomic space correspond to distinct cell types and in some cases-for example, Caenorhabditis elegans neurons1 and retinal ganglion cells2-4-have been shown to share morphology and function. The zebrafish optic tectum is composed of a spatial array of neurons that transforms visual inputs into motor outputs. Although the visuotopic map is continuous, subregions of the tectum are functionally specialized5,6. Here, to uncover the cell-type architecture of the tectum, we transcriptionally profiled its neurons, revealing more than 60 cell types that are organized in distinct anatomical layers. We measured the visual responses of thousands of tectal neurons by two-photon calcium imaging and matched them with their transcriptional profiles. Furthermore, we characterized the morphologies of transcriptionally identified neurons using specific transgenic lines. Notably, we found that neurons that are transcriptionally similar can diverge in shape, connectivity and visual responses. Incorporating the spatial coordinates of neurons within the tectal volume revealed functionally and morphologically defined anatomical subclusters within individual transcriptomic clusters. Our findings demonstrate that extrinsic, position-dependent factors expand the phenotypic repertoire of genetically similar neurons.

Incomplete remyelination via therapeutically enhanced oligodendrogenesis is sufficient to recover visual cortical function

Myelin loss induces neural dysfunction and contributes to the pathophysiology of neurodegenerative diseases, injury conditions, and aging. Because remyelination is often incomplete, better understanding endogenous remyelination and developing remyelination therapies that restore neural function are clinical imperatives. Here, we use in vivo two-photon microscopy and electrophysiology to study the dynamics of endogenous and therapeutic-induced cortical remyelination and functional recovery after cuprizone-mediated demyelination in mice. We focus on the visual pathway, which is uniquely positioned to provide insights into structure-function relationships during de/remyelination. We show endogenous remyelination is driven by recent oligodendrocyte loss and is highly efficacious following mild demyelination, but fails to restore the oligodendrocyte population when high rates of oligodendrocyte loss occur quickly. Testing a thyromimetic (LL-341070) compared to clemastine, we find it better enhances oligodendrocyte gain and hastens recovery of neuronal function. The therapeutic benefit of the thyromimetic is temporally restricted, and it acts exclusively following moderate to severe demyelination, eliminating the endogenous remyelination deficit. However, we find regeneration of oligodendrocytes and myelin to healthy levels is not necessary for recovery of visual neuronal function. These findings advance our understanding of remyelination and its impact on functional recovery to inform future therapeutic strategies.

Enhancer-driven cell type comparison reveals similarities between the mammalian and bird pallium

Combinations of transcription factors govern the identity of cell types, which is reflected by genomic enhancer codes. We used deep learning to characterize these enhancer codes and devised three metrics to compare cell types in the telencephalon across amniotes. To this end, we generated single-cell multiome and spatially resolved transcriptomics data of the chicken telencephalon. Enhancer codes of orthologous nonneuronal and γ-aminobutyric acid-mediated (GABAergic) cell types show a high degree of similarity across amniotes, whereas excitatory neurons of the mammalian neocortex and avian pallium exhibit varying degrees of similarity. Enhancer codes of avian mesopallial neurons are most similar to those of mammalian deep-layer neurons. With this study, we present generally applicable deep learning approaches to characterize and compare cell types on the basis of genomic regulatory sequences.

Developmental origins and evolution of pallial cell types and structures in birds

Innovations in the pallium likely facilitated the evolution of advanced cognitive abilities in birds. We therefore scrutinized its cellular composition and evolution using cell type atlases from chicken, mouse, and nonavian reptiles. We found that the avian pallium shares most inhibitory neuron types with other amniotes. Whereas excitatory neuron types in amniote hippocampal regions show evolutionary conservation, those in other pallial regions have diverged. Neurons in the avian mesopallium display gene expression profiles akin to the mammalian claustrum and deep cortical layers, while certain nidopallial cell types resemble neurons in the piriform cortex. Lastly, we observed substantial gene expression convergence between the dorsally located hyperpallium and ventrally located nidopallium during late development, suggesting that topological location does not always dictate gene expression programs determining functional properties in the adult avian pallium.

Transcriptomic cell-type specificity of local cortical circuits

Complex neocortical functions rely on networks of diverse excitatory and inhibitory neurons. While local connectivity rules between major neuronal subclasses have been established, the specificity of connections at the level of transcriptomic subtypes remains unclear. We introduce single transcriptome assisted rabies tracing (START), a method combining monosynaptic rabies tracing and single-nuclei RNA sequencing to identify transcriptomic cell types, providing inputs to defined neuron populations. We employ START to transcriptomically characterize inhibitory neurons providing monosynaptic input to 5 different layer-specific excitatory cortical neuron populations in mouse primary visual cortex (V1). At the subclass level, we observe results consistent with findings from prior studies that resolve neuronal subclasses using antibody staining, transgenic mouse lines, and morphological reconstruction. With improved neuronal subtype granularity achieved with START, we demonstrate transcriptomic subtype specificity of inhibitory inputs to various excitatory neuron subclasses. These results establish local connectivity rules at the resolution of transcriptomic inhibitory cell types.

Adapting to time: Why nature may have evolved a diverse set of neurons

Brains have evolved diverse neurons with varying morphologies and dynamics that impact temporal information processing. In contrast, most neural network models use homogeneous units that vary only in spatial parameters (weights and biases). To explore the importance of temporal parameters, we trained spiking neural networks on tasks with varying temporal complexity, holding different parameter subsets constant. We found that adapting conduction delays is crucial for solving all test conditions under tight resource constraints. Remarkably, these tasks can be solved using only temporal parameters (delays and time constants) with constant weights. In more complex spatio-temporal tasks, an adaptable bursting parameter was essential. Overall, allowing adaptation of both temporal and spatial parameters enhances network robustness to noise, a vital feature for biological brains and neuromorphic computing systems. Our findings suggest that rich and adaptable dynamics may be the key for solving temporally structured tasks efficiently in evolving organisms, which would help explain the diverse physiological properties of biological neurons.

Serotonin Inhibition of Claustrum Projection Neurons: Ionic Mechanism, Receptor Subtypes and Consequences for Claustrum Computation

The claustrum is a small but densely interconnected brain structure that is innervated by axons containing serotonin (5-HT), a neuromodulator that has been implicated in control of sleep and in the actions of psychedelic drugs. However, little is known about how 5-HT influences the claustrum. We have combined whole-cell patch-clamp measurements of ionic currents, flash photolysis, and receptor pharmacology to characterize the 5-HT responses of individual claustral projection neurons (PNs) in mouse brain slices. Serotonin application elicited a long-lasting outward current in claustral PNs. This current was due to an increase in membrane permeability to K+ ions and was mediated mainly by the type 1A 5-HT receptor (5-HTR-1A). The 5-HT-induced K+ current hyperpolarized, and thereby inhibited, the PNs by reducing action potential firing. Focal uncaging of 5-HT revealed that inhibitory 5-HTR-1As were located at both the soma and dendrites of PNs. We conclude that 5-HT creates a net inhibition in the claustrum, an action that should decrease claustrum sensitivity to excitatory input from other brain areas and thereby contribute to 5-HT action in the brain.

Neuronal diversity and stereotypy at multiple scales through whole brain morphometry

We conducted a large-scale whole-brain morphometry study by analyzing 3.7 peta-voxels of mouse brain images at the single-cell resolution, producing one of the largest multi-morphometry databases of mammalian brains to date. We registered 204 mouse brains of three major imaging modalities to the Allen Common Coordinate Framework (CCF) atlas, annotated 182,497 neuronal cell bodies, modeled 15,441 dendritic microenvironments, characterized the full morphology of 1876 neurons along with their axonal motifs, and detected 2.63 million axonal varicosities that indicate potential synaptic sites. Our analyzed six levels of information related to neuronal populations, dendritic microenvironments, single-cell full morphology, dendritic and axonal arborization, axonal varicosities, and sub-neuronal structural motifs, along with a quantification of the diversity and stereotypy of patterns at each level. This integrative study provides key anatomical descriptions of neurons and their types across a multiple scales and features, contributing a substantial resource for understanding neuronal diversity in mammalian brains.

Claustrum modulation drives altered prefrontal cortex dynamics and connectivity

This study delves into the claustrum's role in modulating spontaneous and sensory-evoked network activity across cortical regions. Using mesoscale calcium imaging and Gi and Gq DREADDs in anesthetized mice, we show that decreasing claustral activity enhances prefrontal cortical activity, while activation reduces prefrontal cortical activity. This claustrum modulation also caused changes to the brain's large-scale functional networks, emphasizing the claustrum's ability to influence long-range functional connectivity in the cortex. Claustrum inhibition increased the local coupling between frontal cortex areas, but reduced the correlation between anterior medial regions and lateral/posterior regions, while also enhancing sensory-evoked responses in the visual cortex. These findings indicate the claustrum can participate in orchestrating neural communication across cortical regions through modulation of prefrontal cortical activity. These insights deepen our understanding of the claustrum's impact on prefrontal connectivity, large-scale network dynamics, and sensory processing, positioning the claustrum as a key node modulating large-scale cortical dynamics.

A consensus definition for deep layer 6 excitatory neurons in mouse neocortex

To understand neocortical function, we must first define its cell types. Recent studies indicate that neurons in the deepest cortical layer play roles in mediating thalamocortical interactions and modulating brain state and are implicated in neuropsychiatric disease. However, understanding the functions of deep layer 6 (L6b) neurons has been hampered by the lack of agreed upon definitions for these cell types. We compared commonly used methods for defining L6b neurons, including molecular, transcriptional and morphological approaches as well as transgenic mouse lines, and identified a core population of L6b neurons. This population does not innervate sensory thalamus, unlike layer 6 corticothalamic neurons (L6CThNs) in more superficial layer 6. Rather, single L6b neurons project ipsilaterally between cortical areas. Although L6b neurons undergo early developmental changes, we found that their intrinsic electrophysiological properties were stable after the first postnatal week. Our results provide a consensus definition for L6b neurons, enabling comparisons across studies.

Genetic risk factors underlying white matter hyperintensities and cortical atrophy

White matter hyperintensities index structural abnormalities in the cerebral white matter, including axonal damage. The latter may promote atrophy of the cerebral cortex, a key feature of dementia. Here, we report a study of 51,065 individuals from 10 cohorts demonstrating that higher white matter hyperintensity volume associates with lower cortical thickness. The meta-GWAS of white matter hyperintensities-associated cortical 'atrophy' identifies 20 genome-wide significant loci, and enrichment in genes specific to vascular cell types, astrocytes, and oligodendrocytes. White matter hyperintensities-associated cortical 'atrophy' showed positive genetic correlations with vascular-risk traits and plasma biomarkers of neurodegeneration, and negative genetic correlations with cognitive functioning. 15 of the 20 loci regulated the expression of 54 genes in the cerebral cortex that, together with their co-expressed genes, were enriched in biological processes of axonal cytoskeleton and intracellular transport. The white matter hyperintensities-cortical thickness associations were most pronounced in cortical regions with higher expression of genes specific to excitatory neurons with long-range axons traversing through the white matter. The meta-GWAS-based polygenic risk score predicts vascular and all-cause dementia in an independent sample of 500,348 individuals. Thus, the genetics of white matter hyperintensities-related cortical atrophy involves vascular and neuronal processes and increases dementia risk.

Reimagining Cortical Connectivity by Deconstructing Its Molecular Logic into Building Blocks

Comprehensive maps of neuronal connectivity provide a foundation for understanding the structure of neural circuits. In a circuit, neurons are diverse in morphology, electrophysiology, gene expression, activity, and other neuronal properties. Thus, constructing a comprehensive connectivity map requires associating various properties of neurons, including their connectivity, at cellular resolution. A commonly used approach is to use the gene expression profiles as an anchor to which all other neuronal properties are associated. Recent advances in genomics and anatomical techniques dramatically improved the ability to determine and associate the long-range projections of neurons with their gene expression profiles. These studies revealed unprecedented details of the gene-projection relationship, but also highlighted conceptual challenges in understanding this relationship. In this article, I delve into the findings and the challenges revealed by recent studies using state-of-the-art neuroanatomical and transcriptomic techniques. Building upon these insights, I propose an approach that focuses on understanding the gene-projection relationship through basic features in gene expression profiles and projections, respectively, that associate with underlying cellular processes. I then discuss how the developmental trajectories of projections and gene expression profiles create additional challenges and necessitate interrogating the gene-projection relationship across time. Finally, I explore complementary strategies that, together, can provide a comprehensive view of the gene-projection relationship.

Consciousness and Energy Processing in Neural Systems

BACKGROUND

Our understanding of the relationship between neural activity and psychological states has advanced greatly in recent decades. But we are still unable to explain conscious experience in terms of physical processes occurring in our brains.

METHODS

This paper introduces a conceptual framework that may contribute to an explanation. All physical processes entail the transfer, transduction, and transformation of energy between portions of matter as work is performed in material systems. If the production of consciousness in nervous systems is a physical process, then it must entail the same. Here the nervous system, and the brain in particular, is considered as a material system that transfers, transduces, and transforms energy as it performs biophysical work.

CONCLUSIONS

Evidence from neuroscience suggests that conscious experience is produced in the organic matter of nervous systems when they perform biophysical work at classical and quantum scales with a certain level of dynamic complexity or organization. An empirically grounded, falsifiable, and testable hypothesis is offered to explain how energy processing in nervous systems may produce conscious experience at a fundamental physical level.

Beyond Barrels: Diverse Thalamocortical Projection Motifs in the Mouse Ventral Posterior Complex

Thalamocortical pathways from the rodent ventral posterior (VP) thalamic complex to the somatosensory cerebral cortex areas are a key model in modern neuroscience. However, beyond the intensively studied projection from medial VP (VPM) to the primary somatosensory area (S1), the wiring of these pathways remains poorly characterized. We combined micropopulation tract-tracing and single-cell transfection experiments to map the pathways arising from different portions of the VP complex in male mice. We found that pathways originating from different VP regions show differences in area/lamina arborization pattern and axonal varicosity size. Neurons from the rostral VPM subnucleus innervate trigeminal S1 in point-to-point fashion. In contrast, a caudal VPM subnucleus innervates heavily and topographically second somatosensory area (S2), but not S1. Neurons in a third, intermediate VPM subnucleus innervate through branched axons both S1 and S2, with markedly different laminar patterns in each area. A small anterodorsal subnucleus selectively innervates dysgranular S1. The parvicellular VPM subnucleus selectively targets the insular cortex and adjacent portions of S1 and S2. Neurons in the rostral part of the lateral VP nucleus (VPL) innervate spinal S1, while caudal VPL neurons simultaneously target S1 and S2. Rostral and caudal VP nuclei show complementary patterns of calcium-binding protein expression. In addition to the cortex, neurons in caudal VP subnuclei target the sensorimotor striatum. Our finding of a massive projection from VP to S2 separate from the VP projections to S1 adds critical anatomical evidence to the notion that different somatosensory submodalities are processed in parallel in S1 and S2.

Developmental mouse brain common coordinate framework

3D brain atlases are key resources to understand the brain's spatial organization and promote interoperability across different studies. However, unlike the adult mouse brain, the lack of developing mouse brain 3D reference atlases hinders advancements in understanding brain development. Here, we present a 3D developmental common coordinate framework (DevCCF) spanning embryonic day (E)11.5, E13.5, E15.5, E18.5, and postnatal day (P)4, P14, and P56, featuring undistorted morphologically averaged atlas templates created from magnetic resonance imaging and co-registered high-resolution light sheet fluorescence microscopy templates. The DevCCF with 3D anatomical segmentations can be downloaded or explored via an interactive 3D web-visualizer. As a use case, we utilize the DevCCF to unveil GABAergic neuron emergence in embryonic brains. Moreover, we map the Allen CCFv3 and spatial transcriptome cell-type data to our stereotaxic P56 atlas. In summary, the DevCCF is an openly accessible resource for multi-study data integration to advance our understanding of brain development.

Cell class-specific long-range axonal projections of neurons in mouse whisker-related somatosensory cortices

Long-range axonal projections of diverse classes of neocortical excitatory neurons likely contribute to brain-wide interactions processing sensory, cognitive and motor signals. Here, we performed light-sheet imaging of fluorescently labeled axons from genetically defined neurons located in posterior primary somatosensory barrel cortex and supplemental somatosensory cortex. We used convolutional networks to segment axon-containing voxels and quantified their distribution within the Allen Mouse Brain Atlas Common Coordinate Framework. Axonal density was analyzed for different classes of glutamatergic neurons using transgenic mouse lines selectively expressing Cre recombinase in layer 2/3 intratelencephalic projection neurons (Rasgrf2-dCre), layer 4 intratelencephalic projection neurons (Scnn1a-Cre), layer 5 intratelencephalic projection neurons (Tlx3-Cre), layer 5 pyramidal tract projection neurons (Sim1-Cre), layer 5 projection neurons (Rbp4-Cre), and layer 6 corticothalamic neurons (Ntsr1-Cre). We found distinct axonal projections from the different neuronal classes to many downstream brain areas, which were largely similar for primary and supplementary somatosensory cortices. Functional connectivity maps obtained from optogenetic activation of sensory cortex and wide-field imaging revealed topographically organized evoked activity in frontal cortex with neurons located more laterally in somatosensory cortex signaling to more anteriorly located regions in motor cortex, consistent with the anatomical projections. The current methodology therefore appears to quantify brain-wide axonal innervation patterns supporting brain-wide signaling.

From Individual to Population: Circuit Organization of Pyramidal Tract and Intratelencephalic Neurons in Mouse Sensorimotor Cortex

The sensorimotor cortex participates in diverse functions with different reciprocally connected subregions and projection-defined pyramidal neuron types therein, while the fundamental organizational logic of its circuit elements at the single-cell level is still largely unclear. Here, using mouse Cre driver lines and high-resolution whole-brain imaging to selectively trace the axons and dendrites of cortical pyramidal tract (PT) and intratelencephalic (IT) neurons, we reconstructed the complete morphology of 1,023 pyramidal neurons and generated a projectome of 6 subregions within the sensorimotor cortex. Our morphological data revealed substantial hierarchical and layer differences in the axonal innervation patterns of pyramidal neurons. We found that neurons located in the medial motor cortex had more diverse projection patterns than those in the lateral motor and sensory cortices. The morphological characteristics of IT neurons in layer 5 were more complex than those in layer 2/3. Furthermore, the soma location and morphological characteristics of individual neurons exhibited topographic correspondence. Different subregions and layers were composed of different proportions of projection subtypes that innervate downstream areas differentially. While the axonal terminals of PT neuronal population in each cortical subregion were distributed in specific subdomains of the superior colliculus (SC) and zona incerta (ZI), single neurons selectively innervated a combination of these projection targets. Overall, our data provide a comprehensive list of projection types of pyramidal neurons in the sensorimotor cortex and begin to unveil the organizational principle of these projection types in different subregions and layers.

Continuous cell type diversification throughout the embryonic and postnatal mouse visual cortex development

The mammalian cortex is composed of a highly diverse set of cell types and develops through a series of temporally regulated events that build out the cell type and circuit foundation for cortical function. The mechanisms underlying the development of different cell types remain elusive. Single-cell transcriptomics provides the capacity to systematically study cell types across the entire temporal range of cortical development. Here, we present a comprehensive and high-resolution transcriptomic and epigenomic cell type atlas of the developing mouse visual cortex. The atlas was built from a single-cell RNA-sequencing dataset of 568,674 high-quality single-cell transcriptomes and a single-nucleus Multiome dataset of 194,545 high-quality nuclei providing both transcriptomic and chromatin accessibility profiles, densely sampled throughout the embryonic and postnatal developmental stages from E11.5 to P56. We computationally reconstructed a transcriptomic developmental trajectory map of all excitatory, inhibitory, and non-neuronal cell types in the visual cortex, identifying branching points marking the emergence of new cell types at specific developmental ages and defining molecular signatures of cellular diversification. In addition to neurogenesis, gliogenesis and early postmitotic maturation in the embryonic stage which gives rise to all the cell classes and nearly all subclasses, we find that increasingly refined cell types emerge throughout the postnatal differentiation process, including the late emergence of many cell types during the eye-opening stage (P11-P14) and the onset of critical period (P21), suggesting continuous cell type diversification at different stages of cortical development. Throughout development, we find cooperative dynamic changes in gene expression and chromatin accessibility in specific cell types, identifying both chromatin peaks potentially regulating the expression of specific genes and transcription factors potentially regulating specific peaks. Furthermore, a single gene can be regulated by multiple peaks associated with different cell types and/or different developmental stages. Collectively, our study provides the most detailed dynamic molecular map directly associated with individual cell types and specific developmental events that reveals the molecular logic underlying the continuous refinement of cell type identities in the developing visual cortex.

Molecular programs guiding arealization of descending cortical pathways

Layer 5 extratelencephalic (ET) neurons are present across neocortical areas and send axons to multiple subcortical targets1-6. Two cardinal subtypes exist7,8: (1) Slco2a1-expressing neurons (ETdist), which predominate in the motor cortex and project distally to the pons, medulla and spinal cord; and (2) Nprs1- or Hpgd-expressing neurons (ETprox), which predominate in the visual cortex and project more proximally to the pons and thalamus. An understanding of how area-specific ETdist and ETprox emerge during development is important because they are critical for fine motor skills and are susceptible to spinal cord injury and amyotrophic lateral sclerosis9-12. Here, using cross-areal mapping of axonal projections in the mouse neocortex, we identify the subtype-specific developmental dynamics of ET neurons. Whereas subsets of ETprox emerge by pruning of ETdist axons, others emerge de novo. We outline corresponding subtype-specific developmental transcriptional programs using single-nucleus sequencing. Leveraging these findings, we use postnatal in vivo knockdown of subtype-specific transcription factors to reprogram ET neuron connectivity towards more proximal targets. Together, these results show the functional transcriptional programs driving ET neuron diversity and uncover cell subtype-specific gene regulatory networks that can be manipulated to direct target specificity in motor corticofugal pathways.

Collaborative augmented reconstruction of 3D neuron morphology in mouse and human brains

Digital reconstruction of the intricate 3D morphology of individual neurons from microscopic images is a crucial challenge in both individual laboratories and large-scale projects focusing on cell types and brain anatomy. This task often fails in both conventional manual reconstruction and state-of-the-art artificial intelligence (AI)-based automatic reconstruction algorithms. It is also challenging to organize multiple neuroanatomists to generate and cross-validate biologically relevant and mutually agreed upon reconstructions in large-scale data production. Based on collaborative group intelligence augmented by AI, we developed a collaborative augmented reconstruction (CAR) platform for neuron reconstruction at scale. This platform allows for immersive interaction and efficient collaborative editing of neuron anatomy using a variety of devices, such as desktop workstations, virtual reality headsets and mobile phones, enabling users to contribute anytime and anywhere and to take advantage of several AI-based automation tools. We tested CAR's applicability for challenging mouse and human neurons toward scaled and faithful data production.

Neuronal subtype-specific transcriptomic changes in the cerebral neocortex associated with sleep pressure

Sleep is homeostatically regulated by sleep pressure, which increases during wakefulness and dissipates during sleep. Recent studies have suggested that the cerebral neocortex, a six-layered structure composed of various layer- and projection-specific neuronal subtypes, is involved in the representation of sleep pressure governed by transcriptional regulation. Here, we examined the transcriptomic changes in neuronal subtypes in the neocortex upon increased sleep pressure using single-nucleus RNA sequencing datasets and predicted the putative intracellular and intercellular molecules involved in transcriptome alterations. We revealed that sleep deprivation (SD) had the greatest effect on the transcriptome of layer 2 and 3 intratelencephalic (L2/3 IT) neurons among the neocortical glutamatergic neuronal subtypes. The expression of mutant SIK3 (SLP), which is known to increase sleep pressure, also induced profound changes in the transcriptome of L2/3 IT neurons. We identified Junb as a candidate transcription factor involved in the alteration of the L2/3 IT neuronal transcriptome by SD and SIK3 (SLP) expression. Finally, we inferred putative intercellular ligands, including BDNF, LSAMP, and PRNP, which may be involved in SD-induced alteration of the transcriptome of L2/3 IT neurons. We suggest that the transcriptome of L2/3 IT neurons is most impacted by increased sleep pressure among neocortical glutamatergic neuronal subtypes and identify putative molecules involved in such transcriptional alterations.

BALB/c mice challenged with SARS-CoV-2 B.1.351 β variant cause pathophysiological and neurological changes within the lungs and brains

Up to one-third of individuals suffering from acute SARS-CoV-2 infection with the onset of severe-to-mild diseases could develop several symptoms of neurological disorders, which could last long after resolving the infection, known as neuro-COVID. Effective therapeutic treatments for neuro-COVID remain unavailable, in part, due to the absence of animal models for studying its underlying mechanisms and developing medical countermeasures against it. Here, we explored the impact of SARS-CoV-2 infection on the well-being of respiratory and neurological functions of BALB/c mice by using a clinical isolate of β-variant, i.e. B.1.351. We found that this β-variant of SARS-CoV-2 primarily infected the lungs, causing tissue damage, profound inflammatory responses, altered respiratory functions and transient but significant hypoxia. Although live progeny viruses could not be isolated, viral RNAs were detected across many anatomical regions of the brains in most challenged mice and triggered activation of genes encoding for NF-kB, IL-6, IP-10 and RANTES and microglial cells. We noted that the significantly activated IL-6-encoded gene persisted at 4 weeks after infection. Together, these results suggest that this B.1.351/BALB/c model of SARS-CoV-2 infection warrants further studies to establish it as a desirable model for studies of neuropathogenesis and the development of effective therapeutics of neuro-COVID.

Massive multiplexing of spatially resolved single neuron projections with axonal BARseq

Neurons in the cortex are heterogeneous, sending diverse axonal projections to multiple brain regions. Unraveling the logic of these projections requires single-neuron resolution. Although a growing number of techniques have enabled high-throughput reconstruction, these techniques are typically limited to dozens or at most hundreds of neurons per brain, requiring that statistical analyses combine data from different specimens. Here we present axonal BARseq, a high-throughput approach based on reading out nucleic acid barcodes using in situ RNA sequencing, which enables analysis of even densely labeled neurons. As a proof of principle, we have mapped the long-range projections of >8000 primary auditory cortex neurons from a single male mouse. We identified major cell types based on projection targets and axonal trajectory. The large sample size enabled us to systematically quantify the projections of intratelencephalic (IT) neurons, and revealed that individual IT neurons project to different layers in an area-dependent fashion. Axonal BARseq is a powerful technique for studying the heterogeneity of single neuronal projections at high throughput within individual brains.

A suite of enhancer AAVs and transgenic mouse lines for genetic access to cortical cell types

The mammalian cortex is comprised of cells classified into types according to shared properties. Defining the contribution of each cell type to the processes guided by the cortex is essential for understanding its function in health and disease. We used transcriptomic and epigenomic cortical cell type taxonomies from mouse and human to define marker genes and putative enhancers and created a large toolkit of transgenic lines and enhancer AAVs for selective targeting of cortical cell populations. We report evaluation of fifteen new transgenic driver lines, two new reporter lines, and >800 different enhancer AAVs covering most subclasses of cortical cells. The tools reported here as well as the scaled process of tool creation and modification enable diverse experimental strategies towards understanding mammalian cortex and brain function.

NEURD offers automated proofreading and feature extraction for connectomics

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution. Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML). Automated segmentation methods produce exceptionally accurate reconstructions of cells, but post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons in these volumes contain detailed morphological information at multiple scales, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present "NEURD", a software package that decomposes meshed neurons into compact and extensively-annotated graph representations. With these feature-rich graphs, we automate a variety of tasks such as state of the art automated proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and other annotations. These features enable many downstream analyses of neural morphology and connectivity, making these massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.

Claustrum and dorsal endopiriform cortex complex cell-identity is determined by Nurr1 and regulates hallucinogenic-like states in mice

The Claustrum/dorsal endopiriform cortex complex (CLA) is an enigmatic brain region with extensive glutamatergic projections to multiple cortical areas. The transcription factor Nurr1 is highly expressed in the CLA, but its role in this region is not understood. By using conditional gene-targeted mice, we show that Nurr1 is a crucial regulator of CLA neuron identity. Although CLA neurons remain intact in the absence of Nurr1, the distinctive gene expression pattern in the CLA is abolished. CLA has been hypothesized to control hallucinations, but little is known of how the CLA responds to hallucinogens. After the deletion of Nurr1 in the CLA, both hallucinogen receptor expression and signaling are lost. Furthermore, functional ultrasound and Neuropixel electrophysiological recordings revealed that the hallucinogenic-receptor agonists' effects on functional connectivity between prefrontal and sensorimotor cortices are altered in Nurr1-ablated mice. Our findings suggest that Nurr1-targeted strategies provide additional avenues for functional studies of the CLA.